MLOps Training in Bangalore - MLOps Online Course
                     MLOps Case 
Study: From 
Model 
Development 
to Production
Problem Statement 
& GBuosianelss problem definition
Success metrics and KPIs
Constraints and 
assumptions
Stakeholders and impact
Data Ingestion & 
PrDeatpa asoruarcetsi oannd pipelines
Data validation and cleaning
Feature engineering approach
Train/validation split strategy
Model Development
Algorithm selection 
rationale
Training and 
experimentation
Hyperparameter tuning
Offline evaluation results
Experiment 
Tracking & 
VeTrrascikoinngi rnugns and metrics
Model and data versioning
Reproducibility practices
Artifacts management
CI/CD & 
DeAputloomyamtede bnutild and tests
Containerization strategy
Deployment to 
staging/production
Rollback and blue/green 
strategy
Monitoring & 
ObPseerfrorvmaabncieli atnyd latency 
metrics
Data and concept drift 
detection
Alerts and dashboards
Auto-retraining triggers
Outcomes & 
LeBaursninienssg imspact achieved
Operational improvements
Challenges faced
Best practices adopted
Conclusion
MLOps enables reliable production 
ML
Automation reduces risk and MTTR
Observability is critical post-
deploy
Iterate continuously for success
Contact Us
Flat no: 205, 2nd Floor, NILGIRI 
Block, Aditya Enclave, Ameerpet, 
Hyderabad-16
 Mobile No: +91 7032290546
 [email protected]
THANK 
YOU
WWW.VISUALPATH.COM